1 Introduction

The purpose of this notebook is to visualize the clonal transcriptomic evolution in Richter syndrome.

2 Pre-processing

2.1 Load packages

library(Seurat)
library(SeuratWrappers)
library(harmony)
library(tidyverse)

2.2 Define parameters

# Paths
path_to_12 <- here::here("results/R_objects/6.seurat_annotated_12.rds")
path_to_19 <- here::here("results/R_objects/6.seurat_annotated_19.rds")
path_to_63 <- here::here("results/R_objects/patient_63/3.seurat_annotated.rds")
path_to_365 <- here::here("results/R_objects/6.seurat_annotated_365.rds")
path_to_3299 <- here::here("results/R_objects/6.seurat_annotated_3299.rds")


# Colors
color_palette <- c("black", "gray", "red", "yellow", "violet", "green4",
                   "blue", "mediumorchid2", "coral2", "blueviolet",
                   "indianred4", "deepskyblue1", "dimgray", "deeppink1",
                   "green", "lightgray", "hotpink1")


# Source functions
source(here::here("bin/utils.R"))

2.3 Load data

paths_to_load <- c(
  "12" = path_to_12,
  "19" = path_to_19,
  "63" = path_to_63,
  "365" = path_to_365,
  "3299" = path_to_3299
)
seurat_list <- purrr::map(paths_to_load, readRDS)
seurat_list
## $`12`
## An object of class Seurat 
## 23326 features across 5785 samples within 1 assay 
## Active assay: RNA (23326 features, 2000 variable features)
##  3 dimensional reductions calculated: pca, harmony, umap
## 
## $`19`
## An object of class Seurat 
## 23326 features across 7284 samples within 1 assay 
## Active assay: RNA (23326 features, 2000 variable features)
##  3 dimensional reductions calculated: pca, harmony, umap
## 
## $`63`
## An object of class Seurat 
## 13680 features across 983 samples within 1 assay 
## Active assay: RNA (13680 features, 2000 variable features)
##  2 dimensional reductions calculated: pca, umap
## 
## $`365`
## An object of class Seurat 
## 23326 features across 4685 samples within 1 assay 
## Active assay: RNA (23326 features, 2000 variable features)
##  3 dimensional reductions calculated: pca, harmony, umap
## 
## $`3299`
## An object of class Seurat 
## 23326 features across 6063 samples within 1 assay 
## Active assay: RNA (23326 features, 2000 variable features)
##  3 dimensional reductions calculated: pca, harmony, umap
purrr::map(seurat_list, DimPlot, cols = color_palette)
## $`12`

## 
## $`19`

## 
## $`63`

## 
## $`365`

## 
## $`3299`

3 Clonal evolution

3.1 UMAPs splitted by time point

seurat_list <- purrr::map(seurat_list, function(seurat_obj) {
  seurat_obj@meta.data <- seurat_obj@meta.data %>%
    mutate(sample_description_RM = str_c(
      time_point,
      sample_description_FN,
      sep = "_"
    ))
  seurat_obj
})
umaps_time_points <- purrr::map(names(seurat_list), function(x) {
  p <- plot_split_umap(seurat_list[[x]], "sample_description_RM", pt_size = 0.5) +
    ggtitle(x) +
    theme(plot.title = element_text(size = 13, hjust = 0.5, face = "bold"))
  p
})
names(umaps_time_points) <- names(seurat_list)
umaps_time_points
## $`12`

## 
## $`19`

## 
## $`63`

## 
## $`365`

## 
## $`3299`

3.2 Stacked bar plots

Let us start by computing the proportions of clons across time points:

proportions_dfs <- purrr::map(seurat_list, function(seurat_obj) {
  df <- seurat_obj@meta.data %>%
    select("sample_description_RM", "annotation_final") %>%
    group_by(sample_description_RM, annotation_final) %>%
    summarise(n_cells = n()) %>%
    ungroup() %>%
    group_by(sample_description_RM) %>%
    mutate(n_cells_total = sum(n_cells)) %>%
    ungroup() %>%
    mutate(percentage_cells = round(n_cells / n_cells_total * 100, 3))
  df
})
DT::datatable(proportions_dfs$`12`)
DT::datatable(proportions_dfs$`19`)
DT::datatable(proportions_dfs$`63`)
DT::datatable(proportions_dfs$`365`)
DT::datatable(proportions_dfs$`3299`)

Plots:

stacked_bars_ggs <- purrr::map(names(proportions_dfs), function(x) {
  p <- proportions_dfs[[x]] %>%
    ggplot(aes(sample_description_RM, percentage_cells, fill = annotation_final)) +
      geom_col() +
      ggtitle(x) +
      labs(x = "", y = "Percentage of Cells (%)", fill = "") + 
      scale_fill_manual(values = color_palette) +
      theme_bw() +
      theme(
        plot.title = element_text(size = 13, hjust = 0.5, face = "bold"),
        axis.text.x = element_text(angle = 45, vjust = 1, hjust = 1)
      )
  p
})
names(stacked_bars_ggs) <- names(seurat_list)
stacked_bars_ggs
## $`12`

## 
## $`19`

## 
## $`63`

## 
## $`365`

## 
## $`3299`

4 Session Inforamation

sessionInfo()
## R version 4.0.4 (2021-02-15)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.2 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
## 
## locale:
##  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=es_ES.UTF-8        LC_COLLATE=en_US.UTF-8     LC_MONETARY=es_ES.UTF-8    LC_MESSAGES=en_US.UTF-8    LC_PAPER=es_ES.UTF-8       LC_NAME=C                  LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=es_ES.UTF-8 LC_IDENTIFICATION=C       
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] forcats_0.5.1        stringr_1.4.0        dplyr_1.0.6          purrr_0.3.4          readr_1.4.0          tidyr_1.1.3          tibble_3.1.2         ggplot2_3.3.3        tidyverse_1.3.1      harmony_1.0          Rcpp_1.0.6           SeuratWrappers_0.3.0 SeuratObject_4.0.2   Seurat_4.0.3         BiocStyle_2.18.1    
## 
## loaded via a namespace (and not attached):
##   [1] readxl_1.3.1          backports_1.2.1       plyr_1.8.6            igraph_1.2.6          lazyeval_0.2.2        splines_4.0.4         crosstalk_1.1.1       listenv_0.8.0         scattermore_0.7       digest_0.6.27         htmltools_0.5.1.1     fansi_0.5.0           magrittr_2.0.1        tensor_1.5            cluster_2.1.1         ROCR_1.0-11           remotes_2.4.0         globals_0.14.0        modelr_0.1.8          matrixStats_0.59.0    spatstat.sparse_2.0-0 colorspace_2.0-1      rvest_1.0.0           ggrepel_0.9.1         haven_2.4.1           xfun_0.23             crayon_1.4.1          jsonlite_1.7.2        spatstat.data_2.1-0   survival_3.2-10       zoo_1.8-9             glue_1.4.2            polyclip_1.10-0       gtable_0.3.0          leiden_0.3.8          future.apply_1.7.0    abind_1.4-5           scales_1.1.1          DBI_1.1.1             miniUI_0.1.1.1        viridisLite_0.4.0     xtable_1.8-4          reticulate_1.20       spatstat.core_2.1-2   rsvd_1.0.5            DT_0.18               htmlwidgets_1.5.3     httr_1.4.2            RColorBrewer_1.1-2    ellipsis_0.3.2        ica_1.0-2             farver_2.1.0          pkgconfig_2.0.3       sass_0.4.0           
##  [55] uwot_0.1.10           dbplyr_2.1.1          deldir_0.2-10         here_1.0.1            utf8_1.2.1            labeling_0.4.2        tidyselect_1.1.1      rlang_0.4.11          reshape2_1.4.4        later_1.2.0           munsell_0.5.0         cellranger_1.1.0      tools_4.0.4           cli_2.5.0             generics_0.1.0        broom_0.7.7           ggridges_0.5.3        evaluate_0.14         fastmap_1.1.0         yaml_2.2.1            goftest_1.2-2         knitr_1.33            fs_1.5.0              fitdistrplus_1.1-5    RANN_2.6.1            pbapply_1.4-3         future_1.21.0         nlme_3.1-152          mime_0.10             xml2_1.3.2            compiler_4.0.4        rstudioapi_0.13       plotly_4.9.4          png_0.1-7             spatstat.utils_2.2-0  reprex_2.0.0          bslib_0.2.5.1         stringi_1.6.2         highr_0.9             lattice_0.20-41       Matrix_1.3-4          vctrs_0.3.8           pillar_1.6.1          lifecycle_1.0.0       BiocManager_1.30.15   spatstat.geom_2.1-0   lmtest_0.9-38         jquerylib_0.1.4       RcppAnnoy_0.0.18      data.table_1.14.0     cowplot_1.1.1         irlba_2.3.3           httpuv_1.6.1          patchwork_1.1.1      
## [109] R6_2.5.0              bookdown_0.22         promises_1.2.0.1      KernSmooth_2.23-18    gridExtra_2.3         parallelly_1.26.0     codetools_0.2-18      MASS_7.3-53.1         assertthat_0.2.1      rprojroot_2.0.2       withr_2.4.2           sctransform_0.3.2     mgcv_1.8-36           parallel_4.0.4        hms_1.1.0             grid_4.0.4            rpart_4.1-15          rmarkdown_2.8         Rtsne_0.15            shiny_1.6.0           lubridate_1.7.10